Elastic provisioning of resources via distributed virtualization

ABSTRACT

A multi-layer architecture is provided for elastic provisioning of virtualized computing resources. The multi-layer architecture comprises a physical hardware layer comprising a plurality of physical computing machines, a distributed operating system layer that aggregates and virtualizes the computing resources, and a virtual machine layer that comprises virtual machines provisioned, by the distributed operating system layer, with virtualized computing resources. Elastic provisioning of virtualized computing resources comprising receiving computing resource information of a plurality of physical computing machines, producing virtualized computing resources by aggregating the received computing resource information of the plurality of physical computing machines, and provisioning the virtualized computing resources among a plurality of virtual machines.

BACKGROUND

Existing virtualization technology provides for an abstraction from theunderlying hardware resources of a single physical machine. This allowsa single physical machine to be partitioned into multiple virtualmachines with isolated execution and resource guarantees. However, suchvirtualization technology does not provide for partitioning multiplevirtual machines across multiple physical machines.

Other existing virtualization and cloud computing technologies providefor utilizing resources of multiple machines in a single virtualmachine. However, the resources of the single virtual machine, usingsuch technologies, remain tightly bound to the underlying hardwareresources of the multiple machines.

In addition, failure of physical machines using existing virtualizationand cloud computing technologies is a particular problem. For example,failure of a physical machine can cause a reduction in capability for avirtual machine that utilizes the physical machine. Furthermore,migrating virtual machines across geographically distributed datacenters can be difficult when virtual machines are tightly bound tounderlying hardware resources and when the large size of live memory ofeach system has to be transferred over a network over a long distance.Such migration can be time consuming, cause service delays, andnegatively impact business operations.

Therefore, there exists ample opportunity for improvement intechnologies related to provisioning of resources for virtual machinesacross multiple physical machines, which can be located ingeographically distributed data centers.

SUMMARY

A variety of technologies related to elastic provisioning of virtualizedcomputing resources are applied.

For example, a multi-layer architecture is provided for elasticprovisioning of virtualized computing resources. The multi-layerarchitecture comprises a physical hardware layer comprising a pluralityof physical computing machines, a distributed operating system layerthat aggregates computing resources of the plurality of physicalcomputing machines of the physical hardware layer to produce virtualizedcomputing resources, and a virtual machine layer that comprises aplurality of virtual machines, where each of the plurality of virtualmachines is provisioned virtualized computing resources by thedistributed operating system layer from the virtualized computingresources produced by the distributed operating system layer.

As another example, a method is provided for elastic provisioning ofvirtualized computing resources comprising receiving computing resourceinformation of a plurality of physical computing machines, producingvirtualized computing resources by aggregating the received computingresource information of the plurality of physical computing machines,and provisioning the virtualized computing resources among a pluralityof virtual machines. In a specific implementation, the method forelastic provisioning of virtualized computing resources is performed bya distributed operating system.

As another example, a computer-readable medium storing computerexecutable instructions is provided for causing a computing device toperform a method for elastic provisioning of virtualized computingresources, comprising receiving computing resource information of aplurality of physical computing machines, where the computing resourceinformation of the plurality of physical computing machines comprisesprocessing resource information, memory resource information, andstorage resource information, producing virtualized computing resourcesby aggregating the received computing resource information of theplurality of physical computing machines, and provisioning thevirtualized computing resources among a plurality of virtual machines.

In some implementations, a scheduling module (e.g., in the distributedoperating system layer) is used for receiving instructions from softwarerunning on the plurality of virtual machines, and dynamically assigningthe received instructions to the plurality of physical computingmachines (e.g., which are distributed across multiple data centers).

The foregoing and other features and advantages of the invention willbecome more apparent from the following detailed description, whichproceeds with reference to the accompanying figures.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram depicting an example multi-layer architecturefor elastic provisioning of virtualized computing resources.

FIG. 2 is a block diagram depicting an example distributed operatingsystem environment for elastic provisioning of virtualized computingresources.

FIG. 3 is a block diagram depicting an example distributed operatingsystem environment for elastic provisioning of virtualized computingresources from different data centers.

FIG. 4 is a flowchart showing an example method for elastic provisioningof virtualized computing resources.

FIG. 5 is a flowchart showing an example method for dynamicallyprovisioning additional virtualized computing resources.

FIG. 6 is a block diagram showing an example computing device.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS

The following description is directed to techniques and solutions forelastic provisioning of virtualized computing resources. The varioustechniques and solutions can be used in combination or independently.Different embodiments can implement one or more of the describedtechniques and solutions.

I. Multi-Layer Architecture

In the technologies described herein, a multi-layer architecture is usedfor elastic provisioning of virtualized computing resources. Themulti-layer architecture comprises different physical and/or logicallayers, such as a physical hardware layer, a data center layer, adistributed operating system layer, and/or a virtual machine layer.

In a specific implementation, elastic provisioning of virtualizedcomputing resources is performed in a cloud computing environment.Alternatively, the elastic provisioning of virtualized computingresources can be performed using any environment or technology wherevirtualization is applied.

In some implementations, the multi-layer architecture is a three-layerarchitecture. The three-layer architecture is used for elasticprovisioning of virtualized computing resources. FIG. 1 is a blockdiagram depicting a multi-layer architecture 110 for elasticprovisioning of virtualized computing resources. The multi-layerarchitecture 110 comprises a physical hardware layer 120, a distributedoperating system layer 130, and a virtual machine layer 140.

The physical hardware layer 120 comprises a plurality of physicalcomputing machines (e.g., computer servers or other computing devices).The physical computing machines of the physical hardware layer 120 cancome from a central location (e.g., a single data center of a businessor organization), or from different locations (e.g., from different datacenters, which can be geographically distributed). The plurality ofphysical computing machines supply various computing resources, such asprocessing resources (e.g., central processing unit (CPU) resources),memory resources (e.g., random access memory (RAM) resources), storageresources (e.g., hard drive storage resources), network resources (e.g.,network bandwidth resources), and/or other computing resources.

The distributed operating system layer 130 comprises a distributedoperating system for aggregating computing resources of the plurality ofphysical computing machines of the physical hardware layer 120. Thedistributed operating system layer 130 aggregates the computingresources to produced virtualized computing resources, which are usedfor provisioning virtual machines of the virtual machine layer 140.

The virtual machine layer 140 comprises a plurality of virtual machinesthat that have been provisioned with virtualized computing resources bythe distributed operating system layer 130.

For example, in a specific situation, the physical hardware layer 120could comprise three computer servers, with computing resources asfollows:

Computer server 1: 2 GHz CPU, 4 GB RAM, and 2 TB hard drive storage.

Computer server 2: 3 GHZ CPU, 4 GB RAM, and 3 TB hard drive storage.

Computer server 3: 3 GHZ CPU, 8 GB RAM, and 4 TB hard drive storage.

In this situation, the distributed operating system layer 130 wouldaggregate the computing resources of the three computer servers toproduce the following virtualized computing resources: 6 GHZ of totalprocessing capacity, 16 GB of total RAM capacity, and 9 TB of total harddrive storage capacity. The distributed operating system layer 130 woulduse these virtualized computing resources to provision virtual machinesof the virtual machine layer 140. For example, one virtual machine couldbe provisioned with 1 GHz of CPU capacity, 2 GB of RAM, and 1 TB of harddrive storage, while another virtual machine could be provisioned with 4GHz of CPU capacity, 10 GB of RAM, and 5 TB of hard drive storage.

The distributed operating system layer 130 supports dynamicre-provisioning and re-adjusting of the virtualized computing resourceswhen computing needs of a virtual machine changes. For example, if avirtual machine requires additional computing resources, the distributedoperating system layer 130 can re-provision the virtual machine byadding additional virtualized computing resources.

Because the distributed operating system layer 130 provides anabstraction from the physical computing machines of the physicalhardware layer 120, the distributed operating system layer can providevirtualized resources to provision a virtual machine where thevirtualized resources are greater than the computing resources of anyspecific one of the physical computing machines. This allows a virtualmachine to dynamically scale up or down in virtualized resources asneeded.

In some implementations, the distributed operating system layer 130comprises a scheduling module that is configured to receive instructionsfrom software (e.g., system software, applications, services, and/orother types of software) running on the virtual machines (at the virtualmachine layer 140) and dynamically assign the received instructions tothe plurality of physical computing machines at the physical hardwarelayer 120. For example, the distributed operating system layer 130 candirect CPU instructions from a virtual machine to be executed onprocessors of one or more physical computing machines according to theprovisioning of the virtual machine. The scheduling module can directinstructions to provisioned resources based on properties such ascurrent load (e.g., current CPU utilization of the physical computingmachines) and physical location (e.g., by preferring geographicallynearer physical computing machines and/or nearer physical computingmachines based on network connectivity properties).

Distributed scheduling involves determining where resources are locatedthrough the pool of distributed resources to meet the service demands ofthe requesting virtual machines, and allocating such resources in atransparent manner. In a specific implementation, distributed schedulingis performed, at least in part, using the ant colony optimizationalgorithm. The distributed scheduler makes repeated use of the antcolony optimization techniques for automated learning, self-correction,and allocating resources to meet the service demands.

II. Distributed Operating System Environment

In the techniques and solutions described herein, a distributedoperating system environment is provided for elastic provisioning ofvirtualized computing resources. FIG. 2 is a block diagram depicting anexample distributed operating system environment 200 for elasticprovisioning of virtualized computing resources.

In the environment 200, a number of physical computing machines (210A-C)provide computing resources. The physical computing machines 210A-C canbe part of a physical hardware layer, such as that depicted at 120 inFIG. 1.

In the environment 200, a distributed operating system 220 aggregatesthe computing resources of the physical computing machines 210A-C toprovide virtualized computing resources. The distributed operatingsystem 220 can be part of a distributed operating system layer, such asthat depicted at 130 in FIG. 1.

The environment 200 supports provisioning a number of virtual machines,such as 230A and 230B, from the virtualized computing resources. Theprovisioning is performed by the distributed operating system 220. Thevirtual machines 230A and 230B provide applications and other computingservices 240A and 240B to users. The virtual machines 230A and 230B canbe part of a virtual machine layer, such as that depicted at 140 in FIG.1.

III. Computing Resources from Different Data Centers

In the techniques and solutions described herein, elastic provisioningof virtualized computing resources can be provided from physicalmachines operating at various data centers. FIG. 3 is a block diagramdepicting an example distributed operating system environment 300 forelastic provisioning of virtualized computing resources from differentdata centers.

The environment 300 includes data centers 320A-C. Two of the datacenters (320A and 320B) are located in the same geographic area 310A,and one of the data centers (320C) is located in a different geographicarea 310B (e.g., a different city, state, or country). Each data centerhouses a number of physical computing machines. Data center 320A housesphysical computing machines 330A, data center 320B houses physicalcomputing machines 330B, and data center 320C houses physical computingmachines 330C.

In the environment 300, a distributed operating system 340 aggregatesthe computing resources of the physical computing machines 330A-C fromthe data centers 320A-C to provide virtualized computing resources.Virtualized resources can then be used by the distributed operatingsystem 340 to provision virtual machines. With this arrangement, avirtual machine can utilize virtualized computing resources from anumber of physical computing machines from different data centers, andeven from different data centers located in different geographic areas.For example, a virtual machine could be provisioned, and utilize,processor resources from a physical machine from 330A and a physicalmachine from 330C.

IV. Elastic Provisioning of Virtualized Computing Resources

In the techniques and solutions described herein, methods are providedfor elastic provisioning of virtualized computing resources. FIG. 4depicts an example method 400 for elastic provisioning of virtualizedcomputing resources. For example, the method 400 can be implementedwithin a distributed operating system (e.g., distributed operatingsystem 220 or 340).

At 410, computing resource information is received for physicalcomputing machines. At 420, the computing resource information isaggregated to produce virtualized computing resources. At 430, virtualmachines are provisioned using the virtualized computing resources 420.

In a specific implementation, the receiving 410, producing 420, andprovisioning 430 are performed by a distributed operating system. Thedistributed operating system provides an abstraction of the computingresources of the physical computing machines, and provides a holisticview of the total computing resources obtained by aggregating andvirtualizing the physical computing machine resources.

FIG. 5 depicts an example method 500 for dynamically provisioningadditional virtualized computing resources. At 510, a computing demandincrease is detected for a virtual machine. For example, the increasecan be an increase in CPU utilization, memory utilization, storageutilization, and/or network bandwidth utilization. The detected increasecan be triggered by the utilization exceeding a threshold value.

At 520, virtualized computing resources are dynamically provisioned inresponse to the detected increase 510. For example, in response to anincrease in CPU utilization, additional CPU virtualized resources can beprovisioned to the virtual machine.

In a specific implementation, the detecting 510 and provisioning 520 areperformed by a distributed operating system.

In some implementations, the elastic provisioning techniques and toolsdescribed herein are used to eliminate the need to migrate virtualmachines from one set of physical machines to another (e.g., from onedata center to another). Because the elastic provisioning techniques andtools herein use a distributed operating system to provide virtualizedresources, virtual machines are not bound to any specific physicalmachine resources. Therefore, virtualized computing resources can beprovided by physical machines in different locations (e.g., differentdata centers), and virtualized resources can be re-assigned (e.g.,dynamically provisioned) when needed, such as when specific physicalmachine resources become unavailable (e.g., due to a failure) or whendemand of a virtual machine increases or decreases. For example,additional virtualized computing resources can be assigned to a virtualmachine so that the virtual machine continues to effectively perform itsoperations (e.g., providing applications and/or services).

In some implementations, dynamic scheduling is used to direct or assignvirtual machine computing resource requests to specific physicalcomputing machine resources. In this situation, scheduling is usedbecause the virtualized computing resources are not bound to anyspecific physical machine. For example, if a specific virtual machineneeds to use processor resources, then a scheduler (e.g., a schedulingmodule of the distributed operating system) can direct the processinginstructions to a specific physical machine, or split the processinginstructions across different physical machines.

Since the distributed virtualized environment provides an abstractionlayer over the underlying distributed hardware formed by the aggregationof a plurality of machines (either locally or remotely, or a mix oflocal and remote machines), the scheduler has a holistic view of thetotal available computing resources and is able to assign the computingresources to the virtual machine. It is not necessary for the virtualmachine to know the source of its computing resources.

In some implementations, elastic provisioning of computing resources isperformed using a cloud computing environment in combination withrequisite resources from the available data center resources of anenterprise through the use of virtualization concepts. In thisimplementation, a distributed virtualization scheme is provided wherebycomputing resources (e.g., CPU, memory, storage, network) for a virtualmachine are provisioned from the multiple physical machines across datacenters of an enterprise by providing a combination of layer ofdistributed operating system over the existing hardware infrastructurelayer, and an upper layer of virtualized resources provisioned by thedistributed operating system. The end user application receives as muchvirtual resources provisioned from this virtualization layer as requiredby the application which is provisioned inside a virtual machine. Due tothe provisioning of virtual resources the advantages of virtualization(isolated execution, resource guarantees, such as the high availabilityof VMs, etc. This technique allows the unbinding of a virtual machinefrom the single physical machine boundary through a distributedoperating system, and provides advantages such as reduction of expensivevirtual machine live migration in the event of failure of physicalmachines, near optimal utilization of geographically distributedmultiple data center resources, and better capacity planning due tolarger scale aggregation of data center resources.

V. Computing Devices

The techniques and solutions described herein can be performed bysoftware and/or hardware of a computing environment, such as a computingdevice. For example, computing devices include server computers, desktopcomputers, laptop computers, notebook computers, netbooks, tabletdevices, mobile devices, and other types of computing devices (e.g.,devices such as televisions, media players, or other types ofentertainment devices that comprise computing capabilities such asaudio/video streaming capabilities and/or network access capabilities).The techniques and solutions described herein can be performed in acloud computing environment (e.g., comprising virtual machines andunderlying infrastructure resources).

FIG. 6 illustrates a generalized example of a suitable computingenvironment 600 in which described embodiments, techniques, andtechnologies may be implemented. The computing environment 600 is notintended to suggest any limitation as to scope of use or functionalityof the technology, as the technology may be implemented in diversegeneral-purpose or special-purpose computing environments. For example,the disclosed technology may be implemented using a computing device(e.g., a server, desktop, laptop, hand-held device, mobile device, PDA,etc.) comprising a processing unit, memory, and storage storingcomputer-executable instructions implementing the service levelmanagement technologies described herein. The disclosed technology mayalso be implemented with other computer system configurations, includinghand held devices, multiprocessor systems, microprocessor-based orprogrammable consumer electronics, network PCs, minicomputers, mainframecomputers, a collection of client/server systems, and the like. Thedisclosed technology may also be practiced in distributed computingenvironments where tasks are performed by remote processing devices thatare linked through a communications network. In a distributed computingenvironment, program modules may be located in both local and remotememory storage devices.

With reference to FIG. 6, the computing environment 600 includes atleast one central processing unit 610 and memory 620. In FIG. 6, thismost basic configuration 630 is included within a dashed line. Thecentral processing unit 610 executes computer-executable instructions.In a multi-processing system, multiple processing units executecomputer-executable instructions to increase processing power and assuch, multiple processors can be running simultaneously. The memory 620may be volatile memory (e.g., registers, cache, RAM), non-volatilememory (e.g., ROM, EEPROM, flash memory, etc.), or some combination ofthe two. The memory 620 stores software 680 that can, for example,implement the technologies described herein. A computing environment mayhave additional features. For example, the computing environment 600includes storage 640, one or more input devices 650, one or more outputdevices 660, and one or more communication connections 670. Aninterconnection mechanism (not shown) such as a bus, a controller, or anetwork, interconnects the components of the computing environment 600.Typically, operating system software (not shown) provides an operatingenvironment for other software executing in the computing environment600, and coordinates activities of the components of the computingenvironment 600.

The storage 640 may be removable or non-removable, and includes magneticdisks, magnetic tapes or cassettes, CD-ROMs, CD-RWs, DVDs, or any othertangible storage medium which can be used to store information and whichcan be accessed within the computing environment 600. The storage 640stores instructions for the software 680, which can implementtechnologies described herein.

The input device(s) 650 may be a touch input device, such as a keyboard,keypad, mouse, pen, or trackball, a voice input device, a scanningdevice, or another device, that provides input to the computingenvironment 600. For audio, the input device(s) 650 may be a sound cardor similar device that accepts audio input in analog or digital form, ora CD-ROM reader that provides audio samples to the computing environment600. The output device(s) 660 may be a display, printer, speaker,CD-writer, or another device that provides output from the computingenvironment 600.

The communication connection(s) 670 enable communication over acommunication medium (e.g., a connecting network) to another computingentity. The communication medium conveys information such ascomputer-executable instructions, compressed graphics information, orother data in a modulated data signal.

VI. Example Alternatives and Variations

Although the operations of some of the disclosed methods are describedin a particular, sequential order for convenient presentation, it shouldbe understood that this manner of description encompasses rearrangement,unless a particular ordering is required by specific language set forthbelow. For example, operations described sequentially may in some casesbe rearranged or performed concurrently. Moreover, for the sake ofsimplicity, the attached figures may not show the various ways in whichthe disclosed methods can be used in conjunction with other methods.

Any of the disclosed methods can be implemented as computer-executableinstructions stored on one or more computer-readable media (tangiblecomputer-readable storage media, such as one or more optical mediadiscs, volatile memory components (such as DRAM or SRAM), or nonvolatilememory components (such as hard drives)) and executed on a computingdevice (e.g., any commercially available computer, including smartphones or other mobile devices that include computing hardware). By wayof example, computer-readable media include memory 620 and/or storage640. As should be readily understood, the term computer-readable mediadoes not include communication connections (e.g., 670) such as modulateddata signals.

Any of the computer-executable instructions for implementing thedisclosed techniques as well as any data created and used duringimplementation of the disclosed embodiments can be stored on one or morecomputer-readable media. The computer-executable instructions can bepart of, for example, a dedicated software application or a softwareapplication that is accessed or downloaded via a web browser or othersoftware application (such as a remote computing application). Suchsoftware can be executed, for example, on a single local computer (e.g.,any suitable commercially available computer) or in a networkenvironment (e.g., via the Internet, a wide-area network, a local-areanetwork, a client-server network (such as a cloud computing network), orother such network) using one or more network computers.

For clarity, only certain selected aspects of the software-basedimplementations are described. Other details that are well known in theart are omitted. For example, it should be understood that the disclosedtechnology is not limited to any specific computer language or program.For instance, the disclosed technology can be implemented by softwarewritten in C++, Java, Perl, JavaScript, Adobe Flash, or any othersuitable programming language. Likewise, the disclosed technology is notlimited to any particular computer or type of hardware. Certain detailsof suitable computers and hardware are well known and need not be setforth in detail in this disclosure.

Furthermore, any of the software-based embodiments (comprising, forexample, computer-executable instructions for causing a computing deviceto perform any of the disclosed methods) can be uploaded, downloaded, orremotely accessed through a suitable communication means. Such suitablecommunication means include, for example, the Internet, the World WideWeb, an intranet, software applications, cable (including fiber opticcable), magnetic communications, electromagnetic communications(including RF, microwave, and infrared communications), electroniccommunications, or other such communication means.

The disclosed methods, apparatus, and systems should not be construed aslimiting in any way. Instead, the present disclosure is directed towardall novel and nonobvious features and aspects of the various disclosedembodiments, alone and in various combinations and subcombinations withone another. The disclosed methods, apparatus, and systems are notlimited to any specific aspect or feature or combination thereof, nor dothe disclosed embodiments require that any one or more specificadvantages be present or problems be solved. We therefore claim as ourinvention all that comes within the scope and spirit of these claims.

We claim:
 1. A multi-layer architecture for elastic provisioning ofvirtualized computing resources, the multi-layer architecturecomprising: a physical hardware layer comprising a plurality of physicalcomputing machines; a distributed operating system layer, wherein thedistributed operating system layer aggregates computing resources of theplurality of physical computing machines of the physical hardware layerto produce virtualized computing resources, wherein the virtualizedcomputing resources are not bound to any particular physical computingmachine of the plurality of physical computing machines, and wherein thedistributed operating system layer comprises a scheduling module,wherein the scheduling module is configured to: receive instructionsfrom software running on the plurality of virtual machines; anddynamically assign the received instructions among the plurality ofphysical computing machines; a virtual machine layer, wherein thevirtual machine layer comprises a plurality of virtual machines, andwherein each of the plurality of virtual machines is provisionedvirtualized computing resources by the distributed operating systemlayer from the virtualized computing resources produced by thedistributed operating system layer; and wherein the distributedoperating system layer dynamically re-assigns the virtualized computingresources when a computing demand increase exceeds a threshold value forone of the plurality of the virtual machines by eliminating the need tomigrate the one of the plurality of the virtual machine from one set ofphysical computing machines to another, wherein the plurality ofphysical computing machines are located in a plurality of different datacenters, and wherein the plurality of different data centers comprise atleast two geographically separate data centers.
 2. The multi-layerarchitecture of claim 1 wherein the computing resources compriseprocessing resources, memory resources, storage resources, and networkresources.
 3. The multi-layer architecture of claim 1 wherein themulti-layer architecture is a three-layer architecture.
 4. Themulti-layer architecture of claim 1 wherein at least one virtual machineof the plurality of virtual machines is provisioned virtualizedcomputing resources from at least two physical computing machines of theplurality of physical computing machines.
 5. The multi-layerarchitecture of claim 1 wherein the scheduling module utilizes, at leastin part, an ant colony optimization algorithm.
 6. The multi-layerarchitecture of claim 1 wherein the plurality of virtual machines aredynamically provisioned virtualized computing resources by thedistributed operating system layer, and wherein the multi-layerarchitecture supports re-provisioning virtualized computing resourceswhen one or more physical computing machines of the plurality ofphysical computing machines fail.
 7. The multi-layer architecture ofclaim 1 wherein the multi-layer architecture supports dynamicprovisioning of virtualized computing resources, including provisioningadditional virtualized computing resources to a virtual machine of theplurality of virtual machines when computing demand of the virtualmachine increases.
 8. A method, implemented by a distributed operatingsystem running on one or more computing devices, for elasticprovisioning of virtualized computing resources, the method comprising:receiving, by the distributed operating system, computing resourceinformation of a plurality of physical computing machines; producing, bythe distributed operating system, virtualized computing resources byaggregating the received computing resource information of the pluralityof physical computing machines, wherein the virtualized computingresources are not bound to any particular physical computing machine ofthe plurality of physical computing machines; provisioning, by thedistributed operating system, the virtualized computing resources amonga plurality of virtual machines; scheduling, by a scheduling module ofthe distributed operating system, instructions, wherein the schedulingcomprises: receiving instructions from software running on the pluralityof virtual machines; and dynamically assigning the received instructionsamong the plurality of physical computing machines; detecting, by thedistributed operating system, that computing demand has increased abovea threshold value for a virtual machine of the plurality of virtualmachines; and in response to detecting the increased computing demandabove the threshold value, dynamically re-assigning, by the distributedoperating system, the virtualized computing resources to the virtualmachine which eliminates the need to migrate the virtual machine fromone set of physical computing machines to another, wherein the pluralityof physical computing machines are located in a plurality of differentdata centers, and wherein the plurality of different data centerscomprise at least two geographically separate data centers.
 9. Themethod of claim 8 wherein the computing resource information of theplurality of physical computing machine comprises processing resourceinformation, memory resource information, storage resource information,and network resource information.
 10. The method of claim 8 wherein theprovisioning comprises provisioning at least one virtual machine of theplurality of virtual machines with virtualized computing resources fromat least two physical computing machines of the plurality of physicalcomputing machines.
 11. The method of claim 8 wherein the plurality ofphysical computing machines are located in a plurality of different datacenters.
 12. A computer-readable medium storing computer executableinstructions for causing a computing device to perform a method forelastic provisioning of virtualized computing resources using adistributed operating system, the method comprising: receiving computingresource information of a plurality of physical computing machines,wherein the computing resource information of the plurality of physicalcomputing machines comprises processing resource information, memoryresource information, storage resource information, and network resourceinformation; producing virtualized computing resources by aggregatingthe received computing resource information of the plurality of physicalcomputing machines, wherein the virtualized computing resources are notbound to any particular physical computing machine of the plurality ofphysical computing machines; provisioning the virtualized computingresources among a plurality if virtual machines, and schedulinginstructions, wherein the scheduling comprises: receiving instructionsfrom software running on the plurality of virtual machines; anddynamically assigning the received instructions among the plurality ofphysical computing machines; detecting that computing demand hasincreased above a threshold value for a virtual machine of the pluralityof virtual machines; and in response to detecting the increasedcomputing demand above the threshold value, dynamically re-assigning thevirtualized computing resources to the virtual machine which eliminatesthe need to migrate the virtual machine from one set of physicalcomputing machines to another, wherein the plurality of physicalcomputing machines are located in a plurality of different data centers,and wherein the plurality of different data centers comprise at leasttwo geographically separate data centers.
 13. The computer-readablemedium of claim 12 wherein the provisioning comprises provisioning atleast one virtual machine of the plurality of virtual machines withvirtualized computing resources from at least two physical computingmachines of the plurality of physical computing machines.
 14. Thecomputer-readable medium of claim 12 wherein the plurality of physicalcomputing machines are located in a plurality of different data centers.